scholarly journals Fire and explosion analysis of filling station based on fuzzy mathematics and Bayesian network model

2021 ◽  
Vol 261 ◽  
pp. 03055
Author(s):  
Kezhen Chen ◽  
Jihong Ye ◽  
Xiaofeng Zhang ◽  
Qingqing Lv
Keyword(s):  
Bayesian Network ◽  
Risk Model ◽  
Fault Tree ◽  
Fuzzy Mathematics ◽  
Compressed Natural Gas ◽  
Filling Station ◽  
Fire And Explosion ◽  
Accurate Probability ◽  
Explosion Accidents ◽  
Network Risk

In order to explore the basic events and risk occurrence probability of fire and explosion accidents in CNG (Compressed Natural Gas) filling station, a corresponding Bayesian network risk model was established based on the fault tree of filling station. The prior probability was modified by introducing fuzzy mathematics in the process of transforming the fault tree into Bayesian network, and the posterior probability of the basic events of CNG filling station fire and explosion accidents was analyzed and calculated by GeNIe software. Finally, through case analysis, it is found out that the most dangerous factors that lead to the greatest risk of fire and explosion accidents in a filling station are: personnel misoperation, management defects, etc. After verifying the model, it shows that paying attention to the polymorphism of the base events and determining the rationality of the logical relationship between the base events can calculate the more accurate probability distribution of the base events, and at the same time provide reasonable suggestions for the accident prevention of the gas filling station.

scholarly journals A Bayesian Network risk model for assessing oil spill recovery effectiveness in the ice-covered Northern Baltic Sea

2019 ◽  
Vol 139 ◽  
pp. 440-458 ◽  
Author(s):  
Liangliang Lu ◽  
Floris Goerlandt ◽  
Osiris A. Valdez Banda ◽  
Pentti Kujala ◽  
Anders Höglund ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Baltic Sea ◽  
Oil Spill ◽  
Risk Model ◽  
Network Risk

scholarly journals Accident Cause Factor of Fires and Explosions in Tankers Using Fault Tree Analysis

2021 ◽  
Vol 9 (8) ◽  
pp. 844
Author(s):  
Young-Joong Ahn ◽  
Yong-Ung Yu ◽  
Jong-Kwan Kim
Keyword(s):  
Safety Management ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Tree Analysis ◽  
Management Measures ◽  
Underlying Causes ◽  
Fire And Explosion ◽  
Explosion Accidents ◽  
Atmosphere Environment

Fire and explosion accidents occur frequently in tankers because they transport large quantities of dangerous cargo. To prevent fire and explosion accidents, it is necessary to analyze factors that cause accidents and their effects. In this study, factors that cause fire and explosion accidents were classified using the 4M disaster analysis method, and each factor’s effect on the accident was analyzed using fault tree analysis (FTA). First, the unsafe tank atmosphere environment was identified as a primary cause of fire and explosion accidents in tankers, and the underlying causes of these accidents were investigated. The probability of underlying causes leading to primary causes was derived using an expert survey. The results showed that management and media factors had a greater impact on the unsafe tank atmosphere environment than human factors. To prevent fire and explosion accidents, it is necessary to ensure sufficient working and resting times for seafarers and compliance with procedures and work guidelines. A generalization of the results of present and future studies will enable the identification of the cause and preventive measures for fire and explosion accidents in tankers. Furthermore, this will reduce accidents in tankers and contribute to future safety management measures of ships and companies.

Application of Bayesian Network in Safety Evaluation of Metro Construction

2013 ◽  
Vol 838-841 ◽  
pp. 1463-1468
Author(s):  
Xiang Ke Liu ◽  
Zhi Shen Wang ◽  
Hai Liang Wang ◽  
Jun Tao Wang
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
Posterior Probability ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Safety Evaluation ◽  
Tree Analysis ◽  
Tunnel Blasting ◽  
Better Than

The paper introduced the Bayesian networks briefly and discussed the algorithm of transforming fault tree into Bayesian networks at first, then regarded the structures impaired caused by tunnel blasting construction as a example, introduced the built and calculated method of the Bayesian networks by matlab. Then assumed the probabilities of essential events, calculated the probability of top event and the posterior probability of each essential events by the Bayesian networks. After that the paper contrast the characteristics of fault tree analysis and the Bayesian networks, Identified that the Bayesian networks is better than fault tree analysis in safety evaluation in some case, and provided a valid way to assess risk in metro construction.

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